Thigh ultrasound monitoring identifies muscle atrophy in mechanically ventilated pediatric patients.

Over the last decade, ultrasonography has taken on an increasingly important role in the daily management of critically patients and has recently been proposed as a means of measuring muscle volume and architecture. This study had two main aims: to monitor for the onset of muscle atrophy in mechanically ventilated pediatric patients during stays in a pediatric intensive care unit based on quadriceps femoris muscle thickness measurements and to study whether demographic and clinical variables have an impact on muscle loss in critically children. The study followed a prospective, observational, single-center design. The sample included all children admitted to our pediatric intensive care unit (PICU) who required mechanical ventilation for more than 48 h. Two trained clinicians measured the thickness of the quadriceps using a 12-MHz linear ultrasound transducer within 24 h of initiating invasive mechanical ventilation and again at 72 h, 1 week, and weekly thereafter until extubation. For the entire cohort, quadriceps femoris muscle thickness decreased by 4.67% on average (IQR = -13.4 to -0.59) between the first two assessments and 13% by the time of the final measurement (IQR = -24 to -0.5%) or 1.57%/day (p < 0.001). Approximately half of all the children (23/41; 56%) experienced muscle atrophy (defined a priori as a decrease in thickness of 10% or more). Bivariate analyses revealed that increasing age, being a child (vs. infant), cumulative energy and protein deficit, highest C-reactive protein value, exposure to neuromuscular blockers, and a longer stay in the PICU were all predictive of a greater decrease in thickness. In a multivariate model, exposure to neuromuscular blockers was linked with greater muscle loss.       Conclusion: In mechanically ventilated children, point-of-care ultrasonography can identify skeletal muscle atrophy. Muscle atrophy of limbs is strongly associated with the use of neuromuscular blockers. Ultrasound-based monitoring of the quadriceps femoris is a clinically useful tool for assessing muscle mass that can provide information on nutritional status and guide rehabilitation. What is Known: • ICU-acquired muscle atrophy is common and has a deleterious effect on adult outcomes. The prevalence and severity of muscular atrophy in critically ill children, however, are poorly understood. • Point-of-care ultrasonography has been put forward as an accurate, reliable method for monitoring variations in muscle mass.. What is New: • The quadriceps femoris muscle tends to suffer an intense loss of thickness early on in most critically ill children. • Quadriceps femoris ultrasound monitoring is a helpful tool for measuring muscle thickness and could lead to the development of novel therapies for critically ill children.

Analysis of complications in intraventricular neuroendoscopy in children: proposal for a standardization system.

Although intraventricular neuroendoscopy is considered a minimally invasive technique with good results, there is nevertheless a risk of developing certain complications. As no agreement apparently exists concerning the classification of these complications, we aim to propose a form of classification based on the results of our series, comparing them with recent publications. We undertook a retrospective study of 170 children who underwent intraventricular neuroendoscopy between 2003 and September 2020 at our center. Data were recorded on demographic and clinical variables: age, gender, presenting symptoms, etiology, number of procedures, type of procedure, and complications. Complications were divided into two main groups, intraoperative and postoperative, and in subgroups. The intraoperative complications included one group of systemic alterations and another group of surgical problems. The postoperative complications were divided into six groups: systemic, neurologic, hormone, fluid, hemorrhagic and death. A total of 202 neuroendoscopic procedures were performed in 170 children. The mean age at first surgery was 71 months (22-122). The most common etiology of the hydrocephalus was intraventricular tumors (32.9%), followed by aqueductal stenosis (13.5%). The most usual presenting sign was intracranial hypertension. The procedure most used was third ventriculostomy (62.9%). During the procedures, we experienced 5 surgical intraoperative complications (2.47% per procedure). In the postoperative period, there were 23.7% systemic complications per procedure, 12.87% neurologic, 8.41% hormone, 10.9% fluid, 0.5% hemorrhagic, and 0.99% for postoperative death. The rate of complications associated with intraventricular neuroendoscopy was similar in our series to those already published. Comparative studies require standardization for the analysis of neuroendoscopic complications.

Auscultación asimétrica: lo que la verdad esconde / Asymmetric auscultation: What the truth hides

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Trombosis en cuidados críticos neonatales: nuestra experiencia en 10 años / Thrombosis in intensive care unit: Our experience in 10 years

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Apneas en lactantes con bronquiolitis: incidencia y factores de riesgo para un modelo de predicción / Apnoea in infants with bronchiolitis: Incidence and risk factors for a prediction model

Introducción: La presencia de apneas en la bronquiolitis aguda (BA) varía según las series entre el 1,2 y el 28,8%, y es una de sus complicaciones más temibles. Nuestro objetivo es conocer la incidencia de apneas en pacientes ingresados con diagnóstico de BA y definir sus factores de riesgo asociados para construir un modelo de predicción. Pacientes y método: Estudio observacional retrospectivo de los últimos 5 años de pacientes ingresados en un hospital terciario con diagnóstico de BA según los criterios clásicos. Se recogieron la frecuencia de apneas y las variables clínicas relacionadas, para encontrar factores de riesgo en un modelo de regresión logística binaria para la predicción de apneas. Para evaluar el modelo se elaboró una curva ROC. Resultados: De 1.197 casos, se registró apnea durante el ingreso en 53 (4,4%). Los factores de riesgo incluidos en la ecuación fueron: sexo femenino (OR 0,6; IC del 95%: 0,27-1,37), cesárea (OR: 3,44; IC del 95%: 1,5-7,7), edad posmenstrual ≤ 43 semanas (OR: 6,62; IC del 95%: 2,38-18,7), fiebre (OR: 0,33; IC del 95%: 0,09-1,97), bajo peso al ingreso (OR: 3,06; IC del 95%: 1,23-7,67), apneas antes del ingreso observada por los cuidadores (OR: 5,93; IC del 95%: 2,64-13,3) y sobreinfección bacteriana grave (OR: 3,98; IC del 95%: 1,68-9,46). La sensibilidad y la especificidad óptima del modelo en la curva ROC fueron de 0,842 y 0,846, respectivamente (p < 0,001). Conclusiones: La incidencia de apneas durante el ingreso fue de 4,4 por cada 100 ingresos de BA y año. La ecuación del modelo de predicción estimado puede ser de ayuda al clínico para clasificar a los pacientes con mayor riesgo de apnea durante el ingreso en la BA (AU)

Introduction: The presence of apnoea in acute bronchiolitis (AB) varies between 1.2% and 28.8%, depending on the series, and is one of its most fearsome complications. The aim of this study is to determine the incidence of apnoea in hospitalised patients diagnosed with AB, and to define their associated risk factors in order to construct a prediction model. Patients and method: A retrospective observational study of patients admitted to a tertiary hospital in the last 5 years with a diagnosis of AB, according to the classic criteria. Data was collected on the frequency of apnoea and related clinical variables to find risk factors in a binary logistic regression model for the prediction of apnoea. A ROC curve was developed with the model. Results: Apnoea was recorded during the admission of 53 (4.4%) patients out of a total 1,197 cases found. The risk factors included in the equation were: Female (OR 0.6, 95% CI: 0.27-1.37), Caesarean delivery (OR: 3.44, 95% CI: 1.5-7.7), Postmenstrual age ≤43 weeks (OR: 6.62, 95% CI: 2.38-18.7), Fever (OR: 0.33, 95% CI: 0.09-1.97), Low birth weight (OR: 5.93, 95% CI: 2.23-7.67), Apnoea observed by caregivers before admission (OR: 5.93, 95% CI: 2.64-13.3), and severe bacterial infection (OR: 3.98, 95% CI: 1.68-9.46). The optimal sensitivity and specificity of the model in the ROC curve was 0.842 and 0.846, respectively (P < .001). Conclusions: The incidence of apnoea during admission was 4.4 per 100 admissions of AB and year. The estimated prediction model equation may be of help to the clinician in order to classify patients with increased risk of apnoea during admission due to AB (AU)

[Apnoea in infants with bronchiolitis: Incidence and risk factors for a prediction model]. / Apneas en lactantes con bronquiolitis: incidencia y factores de riesgo para un modelo de predicción.

INTRODUCTION: The presence of apnoea in acute bronchiolitis (AB) varies between 1.2% and 28.8%, depending on the series, and is one of its most fearsome complications. The aim of this study is to determine the incidence of apnoea in hospitalised patients diagnosed with AB, and to define their associated risk factors in order to construct a prediction model. PATIENTS AND METHOD: A retrospective observational study of patients admitted to a tertiary hospital in the last 5 years with a diagnosis of AB, according to the classic criteria. Data was collected on the frequency of apnoea and related clinical variables to find risk factors in a binary logistic regression model for the prediction of apnoea. A ROC curve was developed with the model. RESULTS: Apnoea was recorded during the admission of 53 (4.4%) patients out of a total 1,197 cases found. The risk factors included in the equation were: Female (OR 0.6, 95% CI: 0.27-1.37), Caesarean delivery (OR: 3.44, 95% CI: 1.5-7.7), Postmenstrual age ≤43 weeks (OR: 6.62, 95% CI: 2.38-18.7), Fever (OR: 0.33, 95% CI: 0.09-1.97), Low birth weight (OR: 5.93, 95% CI: 2.23-7.67), Apnoea observed by caregivers before admission (OR: 5.93, 95% CI: 2.64-13.3), and severe bacterial infection (OR: 3.98, 95% CI: 1.68-9.46). The optimal sensitivity and specificity of the model in the ROC curve was 0.842 and 0.846, respectively (P<.001). CONCLUSIONS: The incidence of apnoea during admission was 4.4 per 100 admissions of AB and year. The estimated prediction model equation may be of help to the clinician in order to classify patients with increased risk of apnoea during admission due to AB.